Systems | Development | Analytics | API | Testing

Agentic AI Is Changing How We Work. Fast.

“What do I do with the other 7 hours and 55 minutes of my day?” In this short clip from Test Case Scenario, Angie Jones shares how agentic AI is unlocking next-level productivity for automation engineers. After spinning up a full Selenium testing framework in just minutes using an MCP, Angie found herself with a rare gift: time. And with that time? All the innovation and long-neglected backlog work that once felt out of reach suddenly becomes possible.

Managing PostgreSQL table partitioning in Ruby

If you have the pleasure of working with a Rails app that uses a lot of data like logs, events, and metrics, you’ve probably run into performance issues at some point due to large tables. Deleting high quantities of rows can bring your database server to its knees or slow down queries to unacceptable latencies. PostgreSQL table partitioning is an excellent solution to these sorts of problems.

A Technical Guide To Test Mock Data: Levels, Tools, And Best Practices

Mock data is the backbone of modern software development and testing. It allows developers to simulate real-world scenarios without relying on production data, ensuring security, efficiency, and reliability. Whether you’re testing APIs, building UIs, or stress-testing databases, mock data helps you isolate components, accelerate development, and catch bugs early.

Data & Analytics - Logi Symphony Heritage Introduction

They say dashboards are dead. They say BI is for dinosaurs. They say AI is going to change everything. And they're right. The way applications work, the way people interact with data, it's all getting rewritten. Now, imagine if some of the biggest names in data and analytics over the last twenty five years came together to build something completely new, something designed for this AI first world. Wouldn't that be something? What if we went to the people who pioneered the best and most flexible visualization controls ever created? The ones that powered modern web app and experiences.

Kotlin Extension Functions: Add Functionality Without Modifying Code

Imagine you own a car. It’s reliable, runs smoothly and gets you where you need to go. But one day, you realize you need a GPS navigation system for better routes. What do you do? Would you redesign the entire car just to integrate GPS, or would you simply install a GPS device on the dashboard? Of course, the smarter choice is to add the GPS instead of modifying the car’s built-in system. This is exactly how a Kotlin Extension Function works.

The EU AI Act: Key Implications for Using Data in the Modern Enterprise

The EU AI Act is a new law changing how organisations develop and deploy AI-powered solutions worldwide. Complying with it is a chance for organisations to stand out and build trust with customers through responsible AI use — all while continuing to innovate. As predicted by McKinsey and others back in 2023, AI (specifically generative AI) has become a key part of daily business operations across many industries.

NodeSource N|Solid Runtime Release - May 2025: Performance, Stability & the Final Update for v18

We're excited to share the latest N|Solid Runtime release for May 2025. N|Solid Runtime is the OSS runtime that powers N|Solid. Its a 100% compatible augmented version of Node.js developed by the expert engineers at NodeSource, and it connects with N|Solid to get the most relevant insights of your Node.js application.

Choosing the Right Self-Managed WSO2 API Gateway for Your Needs: Universal, Immutable, and Kubernetes Gateways

As API management continues to evolve alongside the adoption of microservices, IoT, and Kubernetes, selecting the right gateway architecture becomes critical. While WSO2 now offers Bijira, a SaaS-based API management platform, this article focuses exclusively on the self-managed deployment options tailored for on-premises, private cloud, and customer-managed public cloud environments.

Test Smarter, Not Larger: How SLMs Are Outperforming Massive AI Models in QA Efficiency

For years, the tech world has been captivated by the sheer scale of Artificial Intelligence. Headlines trumpet models boasting trillions of parameters, hinting at a future where massive AI effortlessly solves our most complex challenges. Giants like GPT-4 and Gemini Ultra, with their vast architectures, have set the benchmark. Yet, in the specialized arena of software quality assurance, a fascinating counter-narrative is emerging: sometimes, smaller is indeed better.